Same method, different data: rethinking polycentricity in Mazandaran, Iran

Understanding regional spatial structure is crucial for effective planning. This study addresses the key question of whether employing different datasets with the same analytical method yields divergent results in identifying polycentric spatial structures, using the cities of Mazandaran Province, Iran, as a case study. The unequivocal answer is “yes”: the results are not the same. For this purpose, a unified methodology of spatial autocorrelation analysis (Moran’s I) was applied to two fundamental datasets: LandScan population data, representing the demographic fabric (place of residence), and Visible Infrared Imaging Radiometer Suite (VIIRS) nighttime light (NTL) data, representing the economic and infrastructural fabric (place of activity). The findings definitively demonstrate that the choice of data produces different definitions and spatial extents of “center” and “polycentricity.” While a stable core of centers (comprising 13 cities) is common to both analyses, the significant divergence in other areas reveals hidden spatial dynamics. Phenomena, such as “bedroom communities” (demographically dense but economically weak) and “tourism-driven centers” (economically vibrant but with low residential populations) are only identifiable through a comparative analysis of both maps. The results emphasize that Mazandaran’s spatial structure is a dual and multi-layered reality. Consequently, relying on a single data type risks overlooking half of the region’s functional reality (both social and economic) and will lead to incomplete policy-making.